Method and user interface for modifying at least one of contrast and density of pixels of a processed image

ABSTRACT

An image which has been subjected to image processing wherein contrast amplification and density can be specified independently is displayed on a display screen. An initial density level is specified. The contrast of pixels in the displayed image having a density substantially equal to the specified initial density is changed upon movement of an indicium in a first direction and the density of pixels in the displayed image having a density substantially equal to the specified initial density is changed upon movement of the indicium in a second direction.

This application claims the benefit of U.S. Provisional PatentApplication No. 60/484,195, filed Jul. 1, 2003, hereby incorporated byreference. This application also claims the benefit of European PatentApplication No. 03101692.6, filed Jun. 11, 2003, which is incorporatedby reference.

FIELD OF THE INVENTION

The present invention relates to a method of independently modifying atleast one of contrast and density of pixels of an image subjected toprocessing whereby contrast amplification and density can be specifiedindependently.

The invention further relates to a user interface for application ofsuch a method.

BACKGROUND OF THE INVENTION

Nowadays several medical image acquisition techniques and systems existthat render a digital image representation of a medical image, e.g. aradiographic image.

One example of such a system is a computed radiography system wherein aradiation image is recorded on a temporary storage medium, moreparticularly a photostimulable phosphor screen. In such a system adigital image representation is obtained by scanning the screen withradiation of (a) wavelength(s) within the stimulating wavelength rangeof the phosphor and by detecting the light emitted by the phosphor uponstimulation.

Other examples of computed radiography systems are direct radiographysystems, for example systems wherein a radiographic image is recorded ina solid-state sensor comprising a radiation sensitive layer and a layerof electronic read out circuitry.

Still another example of a computed radiography system is a systemwherein a radiographic image is recorded on a conventional X-ray filmand wherein that film is developed and subsequently subjected to imagescanning.

Still other systems such as a tomography system may be envisaged.

The digital image representation of the medical image acquired by one ofthe above systems can then be used for generating a visible image onwhich the diagnosis can be performed. For this purpose the digital imagerepresentation is applied to a hard copy recorder or to a displaydevice.

Commonly the digital image representation is subjected to imageprocessing prior to hard copy recording or display.

In order to convert the digital image information optimally into avisible image on a medium on which the diagnosis is performed, amultiscale image processing method (also called multiresolution imageprocessing method) has been developed by means of which the contrast ofan image is enhanced.

According to this multiscale image processing method an imagerepresented by an array of pixel values is processed by applying thefollowing steps. First the original image is decomposed into a sequenceof detail images at multiple scales and occasionally a residual image.Next, the pixel values of the detail images are modified by applying tothese pixel values at least one nonlinear monotonically increasing oddconversion function with a gradient that gradually decreases withincreasing argument values. Finally, a processed image is computed byapplying a reconstruction algorithm to the residual image and themodified detail images, the reconstruction algorithm being the inverseof the above decomposition process.

The above image processing technique has been described extensively inEuropean patent EP 527 525, the processing being referred to as MUSICAimage processing (MUSICA is a registered trade name of Agfa-GevaertN.V.).

The described method is advantageous over conventional image processingtechniques such as unsharp masking etc. because it increases thevisibility of subtle details in the image and because it increases thefaithfulness of the image reproduction without introducing artefacts.

Prior to being applied to a hard copy recorder or to a display devicethe grey value image is pixelwise converted into a digital imagerepresenting density of the visible image.

The conversion of grey value pixels into density values suitable forreproduction or display comprises the selection of a relevant subrangeof the grey value pixel data and the conversion of the data in thissubrange according to a specific gradation function. Commonly, thegradation function is defined by means of a lookup table, which, foreach grey value, stores the corresponding density value.

Preferably the relevant subrange and the gradation function to beapplied are adapted to the object and to the examination type so thatoptimal and constant image quality can be guaranteed.

The shape of the gradation function is critical. It determines how thesubintervals of the density range of the visible image are associatedwith subranges of grey values, in a monotonic but mostly nonlinear way.

In those intervals where the function is steep, a narrow subrange ofgrey values is mapped onto the available output density interval. On theother hand, in those intervals where the function has a gentle gradient,the available output density interval is shared by a wide subrange ofgrey values. If the gradation function has a gentle gradient in the lowdensity half and evolves to steeper behaviour in the high densityportion, then most of the grey values are mapped to low density, and theoverall appearance of the result image will be bright. Reversely, if thegradation function takes off steeply, and evolves to the high densitywith decreasing gradient, then most of the grey values are mapped tohigh density, yielding a dark, greyish look.

This way, it is possible to determine how the density intervals aredistributed across the range of grey values, by manipulating the shapeof the gradation function. As a general rule, grey value subranges thatare densely populated (i.e. peaks in the grey value histogram) should bemapped onto a wide output density interval. Reversely, intervals of greyvalues that occur infrequently in the image should be concentrated onnarrow density intervals. This paradigm known as histogram equalizationleads to enhanced differentiation of grey value regions in an image.

The density of pixels and image regions is determined by thecorresponding ordinate value of the gradation function. The contrastamplification of pixels and image regions on the other hand, isdetermined by the corresponding derivative value (i.e. the gradient) ofthe gradation function. As a consequence, if the shape of the gradationfunction is adjusted to accommodate a large subrange of grey valueswithin a specified density interval, i.e. if the interval has to copewith wide latitude, then at the same time the contrast in that densityinterval will drop. On the other hand, if a density interval is assignedto only a narrow grey value subrange, then that interval will provideenhanced contrast. If requirements with respect to density and contrastamplification are conflicting, which is often the case, then acompromise is unavoidable.

In one embodiment of the multiscale image processing method as describedin the above-mentioned European patent EP 527 525, the gradationfunction is applied after the reconstruction process, which is theinverse of the multiscale decomposition. The gradation function isapplied to the final scale of reconstruction. As a consequence, thecontrast-to-grey value relationship, which is specified by thederivative of the gradation function, is identical at all scales.

In some cases however, it is favourable to differentiate contrastadjustment depending on grey value and scale simultaneously. E.g. inchest images it is important to have high contrast in the smaller scales(i.e. small scale contrast) at high grey values to enhance conspicuityof pneumothorax, but only moderate small scale contrast in the low greyvalue areas like the mediastum. At the same time, large-scale contrastin the lower and mid grey values must be appropriate to visualise e.g.pleural masses.

In some embodiments disclosed in the above-mentioned European patentapplication EP 527 525 scale-dependent boosting or suppression of thecontribution of detail information is applied.

Two different implementations have been described.

In a first implementation the modified detail images are pixelwisemultiplied by a coefficient in the last stages of the reconstructionprocess. The value of such a coefficient depends on the brightness ofthe pixels of the partially reconstructed image.

In a second implementation a partially reconstructed image is convertedaccording to a monotonically increasing conversion function withgradually decreasing slope, for example a power function. Then thereconstruction process is continued until a full size reconstructedimage is obtained. Finally the resulting image is converted according toa curve that is the inverse of the afore-mentioned conversion curve.

Although this disclosure describes scale-dependent suppression orboosting of the contribution of detail information, it does not describethe way in which an envisaged density nor contrast amplification as afunction of grey value can be obtained.

It is an aspect of the present invention to provide a method ofmodifying at least one of contrast and density of pixels of a processedimage.

It is another aspect of the present invention to provide a userinterface for such methods.

Further aspects will become apparent from the description given below.

SUMMARY OF THE INVENTION

The above mentioned aspects are realised by a method of modifying atleast one of contrast and density of pixels of a processed image as setout in claim 1.

In accordance with the present invention density and contrast in animage are modified independently. In the context of this invention theterm ‘independently’ relates to processing methods in which modificationof contrast does not have substantial influence on the density levels inthe image and wherein modification of the density does not substantiallyinfluence the contrast in the image. Examples of such processing will beelaborated further on.

In the context of the present invention the term indicium refers to amarker, cursor, arrow or the like by means of which a movement with twodegrees of freedom can be executed. This movement will be used tocontrol the change of density or contrast of selected pixels in thedisplayed image without these changes having a mutual influence.

In one embodiment of the present invention an initial density level isspecified by selecting a pixel or pixel region in the displayed imagethat has the envisaged initial density. According to the inventionpixels in the image are modified that have a density value that is equalto or close to that initial density. This embodiment is advantageous inthat the user can easily identify the density which is to be modified orof which the corresponding contrast is to be modified.

Preferably the amount by which contrast or density is changed is largestfor pixels that have a density equal to the specified initial density.The amount by which contrast or density is changed preferably graduallydecreases for selected pixels that have a density which is lower orhigher than the initial density.

Another embodiment of this invention relates to a method of modifying atleast one of contrast and density of the pixels of a processed imagewherein the processed image and at least one of a density axis andcontrast amplification axis of a coordinate system, a density histogramof said processed image, a contrast amplification curve that representscontrast amplification as a function of density applied to obtain saidprocessed image and a movable indicium on said contrast amplificationcurve in a position corresponding with an initial density and contrast,are displayed on a screen.

The indicium is moved in at least one of the directions of said axes.Upon movement of the indicium in the direction of the contrastamplification axis contrast of selected pixels that have a density valuethat is substantially equal to said initial density in the displayedimage is changed. Upon movement of the indicium in the direction of thedensity axis, density of selected pixels that have a density value thatis substantially equal to said initial density in the image is changed.This way, contrast and density are changed independently. Movement ofthe indicium is not restricted to a direction along one of the axes. Anyarbitrary two-dimensional movement in the plane causes a simultaneouschange of contrast and density, in accordance with the magnitudes ofmovement components along both axes.

This embodiment can also be combined with the embodiment of claim 1.

In this embodiment an initial density level can likewise be specified byselecting a pixel or pixel region in the displayed image that has theenvisaged initial density. Pixels are modified that have a density valuethat is equal to or close to that initial density. This embodiment isadvantageous in that the user can easily identify the density which isto be modified or of which the corresponding contrast is to be modified.

In still another embodiment an initial density can be chosen byselecting a working point in the displayed coordinate system.Modifications can be controlled by moving the working point in thedirection of either density or contrast amplification axis, or in adirection that involves simultaneous adjustment of contrast and density

Preferably the amount by which contrast or density is changed is largestfor pixels that have a density equal to the initial density. The amountby which contrast or density is changed preferably gradually decreasesfor selected pixels that have a density which is lower or higher thanthe initial density.

In each embodiment the width of the range of density values that areregarded as substantially equal to the initial density may be set by theoperator and is dependent on the application.

It is furthermore advantageous that the density histogram and/orcontrast amplification curve pertaining to the image obtained as resultof the movement of the indicium is displayed. To this end the originalhistogram and contrast amplification curve may be adapted during themodification process.

The above methods are applicable to images that have been subjected tomultiscale gradation processing as is described further on in this text.However, the method is also applicable to other implementations ofcontrast rendition whereby contrast amplification and density can bespecified independently.

Another aspect of the present invention relates to a user interface foran image processing and display unit.

The user interface comprises

-   -   a window wherein a processed image is displayed,    -   means such as a pointer or cursor operated by an interactive        control device such as a mouse, for specifying an initial        density level,    -   a first indicium movable in at least one of two directions,        whereby movement of said first indicium in a first direction        causes a change of density of pixels that have a density value        that is substantially equal to said initial density and whereby        movement of said first indicium in a second direction causes a        change of contrast of pixels that have a density value that is        substantially equal to said initial density,        whereby contrast and density are changed independently.

In one embodiment the means for specifying an initial density is asecond indicium which is displayed on the screen and which is movableacross the displayed image. The initial density can be specified bymoving this indicium past the image to a pixel or a pixel region havingthat specific density and by selecting the density value of a pixelcovered by the indicium.

In another embodiment the means for specifying an initial density is thesame as the first indicium. In this implementation an initial densitycan for example be selected by indicating with a pointer a pixel havingthat initial density followed by entering this value. Next the samepointer can be moved in a first and a second direction therebyindependently changing the density or contrast of pixels having adensity substantially equal to that initial density.

The width of the range of density values that are regarded assubstantially equal to the initial density may be set by the operatorand is dependent on the application.

In still another embodiment additional items are displayed, e.g. in anadditional window. In this additional window at least one of thefollowing is displayed: a density axis and a contrast amplification axisof a coordinate system, a density histogram of a processed image, acontrast amplification curve that represents contrast amplification as afunction of density applied to obtain said processed image and a thirdindicium on said contrast amplification curve in a positioncorresponding with the initial density and contrast of said processedimage, a density wedge along the density axis.

In this embodiment preferably at least one of the histogram, thecontrast amplification curve and the position of the third indicium isadapted in correspondence with the movement of said second indicium.

Alternatively, the position of said third indicium may be changed and atleast one of the histogram, the contrast amplification curve and theprocessed image is changed upon movement of the third indicium.

The embodiments of the methods of the present invention are generallyimplemented in the form of a computer program product adapted to carryout the method steps of the present invention when run on a computer.The computer program product is commonly stored in a computer readablecarrier medium such as a CD-ROM. Alternatively the computer programproduct takes the form of an electric signal and can be communicated toa user through electronic communication.

The methods in accordance with the present invention are applicable toany kind of monochrome digital images. They are also suited forindependently adjusting the density and contrast of colour images. Tothis end, the colour images comprising three components for each pixel,commonly representing the red, green and blue channel inputs of videoequipment (RGB), are preferably converted into a standard colour spacethat represents hue, saturation and luminance (HSL). If an image isrepresented in this colour space, then the methods in accordance withthe present invention are preferably applied to the luminance componentonly, as if it were a monochrome image. If only this channel isaffected, then the contrast and density can be adjusted withoutintroducing colour distortions.

The method and user interface of the present invention is suited fordisplaying any kind of monochrome and color images obtained from a widevariety of acquisition devices in a wide variety of fields ofapplications wherein interactive modifications of density and/orcontrast can be performed.

Examples of other applications than medical imaging in which the methodand user interface can be applied are the following: modification ofimages obtained by scanning systems and digital cameras in the field ofphotofinishing, in aerial photography, prepress, application to videoimages e.g. for image restoration, digital film paste up on computeretc. The invention is not limited to the enumerated acquisition methodsand enumerated fields of application.

In the method and user interface of the present invention contrast anddensity are changed independently. This can be obtained with processingmethods wherein contrast and density are specified independently.Examples of multiscale gradation processing methods wherein contrast anddensity are specified independently are described below with referenceto the following drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows an apparatus for acquisition of a digital imagerepresentation of a medical image, for processing the digital image andfor generating an enhanced visible image,

FIG. 2 is a block scheme illustrating the image chain,

FIG. 3 illustrates a first embodiment of performing the multiscaledecomposition step, according to the Burt pyramid transform,

FIG. 4 illustrates the corresponding reconstruction step,

FIG. 5 shows an embodiment of multiscale gradation according to a firstmultiscale transform embodiment,

FIG. 6 illustrates a second embodiment of performing the multiscaledecomposition step, according to a dyadic wavelet transform,

FIG. 7 illustrates the corresponding reconstruction step,

FIG. 8 shows an embodiment of multiscale gradation according to thesecond multiscale transform embodiment

FIG. 9 shows the initial scale-specific gradients at large, intermediateand small scales, as a function of grey value.

FIG. 10 illustrates the interactive adjustment of contrast of pixels ina specified density band,

FIG. 11 illustrates the interactive adjustment of density of pixels in aspecified density band,

FIG. 12 illustrates a display window and interactive controls for theadjustment of density and contrast of pixels in a specified densityband, according to a second and third embodiment.

DETAILED DESCRIPTION OF THE INVENTION

Description of an Image Acquisition System

X-rays emitted by a source of radiation (2) are transmitted by a patient(not shown) and recorded on a temporary storage medium, moreparticularly a photostimulable phosphor screen (3). In an identificationstation (4) patient identification data are written into a memorydevice, e.g. an EEPROM provided on a cassette carrying thephotostimulable phosphor screen.

The exposed photostimulable phosphor screen is then fed into a read outapparatus (1) where a digital image representation of the storedradiation image is generated.

For this purpose the exposed screen is scanned by means of radiationhaving (a) wavelength(s) within the stimulation wavelength range of thephotostimulable phosphor.

Image-wise modulated light is emitted by the phosphor upon stimulation.This light is detected and converted by an opto-electronic converter andsubsequent A-to-D converter into a digital image representation of theradiation image.

The digital image representation is applied to an image-processingstation (5) to which is connected an interactive control device such asa mouse (7) and which can be incorporated in the read out device orprovided as a separate workstation. In the image-processing station thedigital image representation is subjected to different kinds ofprocessing, among which are multiscale contrast enhancement, noisereduction and gradation processing. The modification method of thepresent invention is also performed on this processing station.

The processed digital image can also be applied to an output apparatussuch as a hard copy recording device (6) where a visible image isgenerated. The visible image can be used by the radiologist for making adiagnosis.

Image Chain

By means of the terms ‘image chain’ is meant the sequence of imageoperations and image processing control mechanisms that are appliedeither separately or in combination to the digital image representationfor transforming the signal generated by the read out device into aprocessed digital image representation that can be applied to the outputdevice.

A block diagram illustrating the entire image chain is illustrated inFIG. 2.

The image chain comprises the steps enumerated below.

In a preliminary step the digital signal representation of an image issubjected to a conversion according to a square root function, in orderto make the pixel values proportional to the square root of theradiation dose recorded on the photostimulable phosphor screen. Theresulting image is called a raw digital image.

One of the main sources of noise in the image is quantum mottle, whichhas a Poisson distribution. The square root conversion ensures that thenoise statistics is transformed into a Gaussian distribution, with astandard deviation that is independent of dose. The latter preprocessingof the digital image is not essential, but it greatly simplifies themathematics of the subsequent processing stages, because the noise canthen be assumed roughly uniform across the raw image.

In an alternative embodiment, the square root conversion is carried outin the read out apparatus by means of an amplifier with square rootcharacteristic. A raw digital image is generated by applying A-to-Dconversion to the resulting signal.

In still other embodiments, the digital signal representation of animage is converted according to a logarithmic function, or according toa linear function.

With all embodiments, the raw digital image is used for furtherprocessing.

In a first processing step the raw digital image is decomposed into atleast two detail images at successive scales and occasionally a residualimage (further referred to as multiscale representation), according to amultiscale transform. The components of the multiscale representationare referred to as detail images. The pixel values of the multiscalerepresentation correspond with the contrast of elementary imagecomponents, relative to their close neighbourhood.

In the next step the multiscale representation may be subjected to anautomatic gain adjustment procedure to cancel out disturbingfluctuations that are due to dose variations, different exposureparameters, different patient latitude etc, optionally followed by oneor more of steps of reducing excess contrast and enhancing subtlecontrast or edge contrast, as set forth in EP 02102368 filed Sep. 18,2002

Next the processed multiscale representation is subjected to areconstruction step by applying the inverse of the decompositiontransform to the modified detail images.

In the course of reconstruction, a series of scale-specific conversionfunctions are consecutively applied to the partially reconstructedimage, in order to adjust contrast amplification as a function of bothgrey value and scale. The latter process will be referred to asmultiscale gradation. The thus obtained pixel values are the drivingvalues for the hard- or softcopy reproducing device, further on referredto as density values.

1. Multiscale Transform

The raw digital image is subjected to a multiscale decomposition. Theimage is decomposed into at least two detail images representing detailat several successive scales.

This technique has been described extensively in EP 527 525.

The pixels of the detail images represent the amount of variation ofpixel values of the original image at the scale of the detail image,whereby scale refers to spatial extent of these variations.

A residual image can also be generated which is an approximation of theoriginal image with omission of all variations comprised in the detailimages.

The detail images at subsequent scales (or resolution levels) are calledmultiscale layers, or simply layers.

In a first embodiment of computing a multiscale transform the detailimages at successively larger scales are obtained as the result of eachof R iterations of the following steps, as depicted in FIG. 3:

a) computing an approximation image g_(k+1) at a next larger scale k+1by applying a low pass filter LP to the approximation image g_(k)corresponding to the current iteration k, and subsampling the result inproportion to the reduction in spatial frequency bandwidth, usinghowever the original image u₀ as input to said low pass filter in thecourse of the first iteration;

b) computing a detail image b_(k) as the pixelwise difference betweenthe approximation image u_(k) corresponding to the current iteration andthe approximation image u_(k+1) at a next larger scale computedaccording the method sub (a), both images being brought into register byproper interpolation (represented by [↑ LP] in the flow chart) of thelatter image; wherein the residual image u_(R) is equal to theapproximation image produced by the last iteration.

The corresponding reconstruction (which we will refer to as ordinaryreconstruction, i.e. reconstruction without multiscale gradation) isdone by applying the inverse transform, as depicted in FIG. 4. In thedescribed embodiment ordinary reconstruction is implemented by iteratingR times the following procedure starting from the largest scale detailimage b_(R−1) and the residual image v_(R)=u_(R): computing theapproximation image v_(k) at the current scale k by pixelwise adding thedetail image b_(k) at the same scale to the approximation image v_(k+1)at the larger scale corresponding to the previous iteration, both imagesbeing brought into register by proper interpolation of the latter image,using however the residual image v_(R) instead of said larger scaleapproximation image in the course of the first iteration.

The residual image will be a low-resolution image or in the extremecase, an image comprising only one single pixel, depending on the numberof iterations in the decomposition.

The latter combination of forward and inverse multiscale transform iscommonly known as the Burt pyramid transform.

In an alternative embodiment the image is decomposed into a weighted sumof predetermined basic detail images at multiple scales and occasionallya residual basic image by applying a transform to the image, thetransform yielding a set of detail coefficients each expressing therelative contribution to the original image of one of a set of basisfunctions representing these basic detail images and occasionally aresidual coefficient representing the relative contribution to theoriginal image of a basis function representing the basic residualimage.

The basis functions are continuous and non-periodic and have zero meanvalue except for the basis function that represents the basic residualimage. An example of such basis functions are wavelets.

The transform is such that there exists an inverse transform whichreturns the original image or a close approximation thereof when beingapplied to the transform coefficients.

The image can be reconstructed by applying the inverse transform to thedetail coefficients and the residual coefficient if generated.

An example of the alternative embodiment is depicted in FIGS. 6 and 7,where FIG. 6 shows a forward dyadic wavelet transform and FIG. 7 thecorresponding inverse transform.

In the forward transform, shown in FIG. 6, the original image u₀ issplit into a larger-scale approximation image u₁ and a detailcoefficient image b₁ by applying a low-pass analysis filter LP_(a) andhigh-pass analysis filter HP_(a), respectively, followed by subsamplingof both images. This splitting process is repeated R times based on thecurrent approximation image, each time yielding an additional detailcoefficient image and an approximation image at the next larger scale.

The flow chart of the corresponding inverse transform is shown in FIG.7. Starting from the residual image v_(R)=u_(R), which is anapproximation image at the largest scale, an approximation image v_(R−1)at the next smaller scale is computed by upsampling and low-passfiltering the current approximation image v_(R), up-sampling andhigh-pass filtering the detail coefficient image b_(R), and pixelwisesumming the latter results. Subsequent smaller scale approximationimages are obtained by iterating this process R times based on thecurrent approximation image v_(k) and the corresponding detailcoefficient image b_(k).

In a preferred embodiment the high pass filters are directional, e.g.representing grey value transitions in a specific direction. In thatcase, the detail coefficients b_(k) at each scale are partitioned intocoefficients bh_(k), bv_(k), bd_(k), representing either horizontal,vertical and diagonal detail at that scale. Each of the blocks HP_(a)then represents a bank of 3 filters, one for each direction.

2. Reconstruction and Multiscale Gradation

When the (optional) procedures for contrast enhancement shown s in FIG.2 have been performed as described in EP 02102368 filed Sep. 18, 2002,the image is reconstructed by applying to the modified detail images theimage transform that is the inverse of the multiscale decomposition.

Details on the ordinary reconstruction procedure are described higher inthe paragraph relating to image decomposition.

In a first embodiment in accordance with this invention, multiscalegradation is implemented by inserting a series of scale-specificconversion functions in the reconstruction process. At each stage in thereconstruction process where a conversion function is inserted, thelatter is applied to the approximation image at a scale corresponding tothe current iteration, and the result of conversion is used as the inputimage of the next iteration, as described below.

Referring to FIG. 5 which shows a multiscale gradation embodimentaccording to the Burt pyramid transform, the normal inverse transform ismodified as follows.

From the iteration that corresponds with the scale k=L until thesmallest scale k=0, the computed approximation image v_(k) is pixelwiseconverted by a scale-specific conversion function f_(k)( ) before it ispassed to the next iteration.

As to the second multiscale transform embodiment described sub 1, i.e.dyadic wavelet transform, the modification for implementing multiscalegradation is very similar. Referring to FIG. 8, from the iteration thatcorresponds with the scale k=L until the smallest scale k=0, thecomputed approximation image v_(k) is pixelwise converted by ascale-specific conversion function f_(k)( ) before it is passed to thenext iteration.

By an appropriate choice of the series of conversion functions f_(k)( )it is possible to specify the contrast amplification as a function ofgrey value and scale, and to specify grey value-to-density mappingindependently from contrast amplification.

To this end, the scale-specific conversion functions f_(k)( ) aredetermined as will be described below, starting from a series offunctions gm_(k)( ), referred to as scale-specific gradient functions.For a specific scale k, the corresponding scale-specific gradientfunction gm_(k)( ) specifies the amount of contrast amplification atthat scale. Equivalently, the scale-specific gradient function at scalek specifies how much a small pixel value difference (i.e. scale-specificcontrast) at that scale is amplified by the combined effect of allconcatenated conversion functions f_(k)( ) up to the smallest scale k=0.

Also, the scale-specific gradient function gm_(k)( ) specifies to whichextent the finally reconstructed image z₀ is sensitive to a unit detailarising from a pixel with unit value in the corresponding detail image,i.e. b_(k) in case of the Burt pyramid transform, or b_(k+1) in case ofthe dyadic wavelet transform.

The scale-specific gradient functions are equivalent to the partialderivative functions:

${{{gm}_{k}(t)} = \frac{\partial z_{0}}{\partial z_{k + 1}}},{k = 0},1,\ldots\mspace{11mu},L$in which z_(k) represents the image that results from pixelwise applyingthe conversion function f_(k)( ) to the approximation image v_(k), andt=v_(L), i.e. the pixel value of the partially reconstructed image atscale L, which is the largest scale involved in multiscale gradation. Inthe present context, the pixel values t are referred to as thelarge-scale average grey values.

Relying on the concatenation rule for derivation, the scale-specificgradient functions can be written as:gm _(k)(t)=f ₀′(F ₁(t))·f ₁′(F ₂(t))· . . . ·f _(k)′(t),in which f_(k)′(t) represent the derivative functions of thescale-specific conversion functions.

The cumulative conversion functions at subsequent scales are theconcatenation of scale-specific conversion functions f_(k)( ) from thelargest scale L involved in multiscale gradation, up to the scaleconsidered:F _(k)(t)=f _(k) ∘f _(k+1) ∘ . . . ∘f _(L)(t),in which the operator ∘ stands for function concatenation.

The derivative of a cumulative conversion function with respect to t isequal to:F _(k)′(t)=f _(k)′(F _(k+1)(t))·f _(k+1)′(F _(k+2)(t))· . . . ·f_(L)′(t),or equivalently, the derivatives of cumulative conversion functions canbe expressed in terms of scale-specific gradient functions:F ₀′(t)=gm _(L)(t)

${{F_{k}^{\prime}(t)} = {{\frac{{gm}_{L}(t)}{{gm}_{k - 1}(t)}\mspace{14mu} k} = 1}},2,\ldots\mspace{11mu},L$

The cumulative conversion functions are then obtained by integration:

F₀(t) = ∫_(t₀)^(t)gm_(L)(x) ⋅ 𝕕x${{F_{k}(t)} = {{\int_{t_{0}}^{t}{{\frac{{gm}_{L}(x)}{{gm}_{k - 1}(x)} \cdot {\mathbb{d}x}}\mspace{14mu} k}} = 1}},2,\ldots\mspace{11mu},L,$where t₀ is the abscissa t at which F_(k)(t)=0. This parameterdetermines the offset of the cumulative conversion functions. Forconvenience, it may be set to 0; then all cumulative conversionfunctions will cross the origin of the coordinate system.

The scale-specific conversion functions f_(k)( ) are finally obtained byinversion of the cumulative conversion functions F_(k)(t):f _(k)( )=F _(k) ∘F _(k+1) ⁻¹( ), k=0, 1, . . . , L−1f _(L)( )=F _(L)( )

In a preferred embodiment, function inversion is avoided by storing allfunctions in tabular form (i.e. as lookup tables).

First, the tables of scale-specific gradient functions gm_(k)( ) arecomputed in a way that will be described below.

Next, the cumulative conversion functions F_(k)(t) are computed byconventional numerical integration techniques such as the trapezoidalrule, and also stored in tabular form as N equidistant points (t_(i),F_(k)(t_(i))), i=0, 1, . . . , N−1.

Finally, from these tables, the scale-specific conversion functionsf_(k)( ) are easily derived, also in tabular form. The N (abscissa,ordinate) pairs that define the function f_(k)( ) are given by(F_(k+1)(t_(i)), F_(k)(t_(i))), for the scales k=0, 1, . . . , L−1. Atscale L which is the largest scale considered in the multiscalegradation process, the function f_(L)( ) is identical to F_(L)( ). Hencein tabular form the latter is specified by (t_(i), F_(L)(t_(i))).

This way, all scale-specific conversion functions are defined by seriesof points, which in general, are non-equidistant. Therefore, thefunctions f_(k)( ) have to be interpolated in order to be evaluated atarbitrary integer input values.

3. Independent Adjustment of Density and Contrast

In accordance with the process described above, the behaviour ofmultiscale gradation is entirely determined by the shapes of thegradient functions gm_(k)( ) at subsequent scales. Small-scale,medium-scale and large-scale contrast are controlled by specifyingappropriate scale-specific gradient functions, as described below. Inaccordance with the present invention the gradient functions gm_(k)( )have an initial specification gm0 _(k)( ) which is either fixed ordepends on the grey value histogram and which determine the initialdensity and contrast rendering of the image before any adjustment ofdensity or contrast according to the present invention is carried out.Typically, the resulting image is the one that is shown on the displaymonitor of a workstation at the beginning of an interactive adjustmentsession. With each new adjustment of density or contrast amplification anew series of multiscale gradient functions is defined which are denotedby gm_(k)( ), and which specify the density and contrast rendering ofthe image at the current stage of adjustment. Typically one or moresubsequent adjustments of density and contrast may be required to renderan image with optimal density and contrast.

In a preferred embodiment the initial gradient functions are defined asfollows.

3a. Initial Large-scale Gradient Function

The initial large-scale gradient function gm0 _(L)(t) specifies thecontrast amplification at a large scale L, which is the largest scaleinvolved in multiscale gradation. In the absence of smaller scaledetail, i.e. if all detail pixels b_(k) (or b_(k+1) in case of dyadicwavelet transform) are equal to zero at scales k=0, 1, . . . , L−1, thenit also determines how the grey values t of the large-scaleapproximation image v_(L) are mapped onto the density scale y of thevisible image. The integral of the large-scale gradient function is thenequivalent to an ordinary gradation function y_(L)(t) to be applied tothe large-scale grey value image v_(L). In the normal case, i.e. whendetail at smaller scale is actually present, then the integral of thefunction gm0 _(L)(t) still determines the large-scale average densitydistribution of the visible image, which is further modulated bysmaller-scale details.

In a preferred embodiment, the large-scale gradient function gm0 _(L)( )is obtained as the derivative of what will be referred to as the initiallarge-scale gradation function y0 _(L)(t).

${{gm0}_{L}(t)} = {\frac{\mathbb{d}\;}{\mathbb{d}t}{{y0}_{L}(t)}}$

The initial large-scale gradation function is determined as describedbelow.

First, a series of anchor points t_(k) is determined from the grey valuehistogram his(t) of the large-scale grey image v_(L). Each anchor pointcorresponds with a predefined percentile p_(k) of the histogram, i.e.t_(k) are the grey values at which the cumulative histogram is equal top_(k).

Preferably, the number of anchor points nk is quite small, e.g. nk=5,and p_(k)=0%, 15%, 50%, 85%, 100%, for k=0 . . . 4.

The large-scale gradation function is specified by its predefinedordinate values in the anchor points:y0_(L)(t _(k))=y _(k)Preferred ordinate values are y_(k)=3%, 10%, 50%, 90%, 97%, expressed asa percentage of the output range.

The optimal number and position of the anchor points, and thecorresponding ordinate values may vary depending on the kind of images.In the special case where p_(k)=y_(k) for all anchor points, thegradation function is identical to the gradation function obtained byglobal histogram equalisation.

The gradation function is defined by fitting a piecewise polynomialfunction such as a spline or a Bezier curve to the predefined anchorpoints. It is extrapolated beyond the range [t₀, t_(nk−1)] by linearextension segments having predefined slopes g₀ and g_(nk−1)respectively.

In an alternative embodiment, the grey value histogram is restricted toa subset of image pixels indicated by a binary image mask, that arejudged to belong to a relevant image regions based on criteria such aslocal contrast to noise ratio, by a method such as described in EP02102368 filed Sep. 18, 2002.

3b. Initial Small-scale Gradient Function

At the smaller scales, the so-called initial small-scale gradientfunction gm0_(S)(t) has a predefined shape. The value of this functionspecifies to which amount the contrast of fine details will be amplifiedas a function of grey value. Hence, by explicitly defining the shape ofthis function, it is possible to enforce specific small scale contrastbehaviour across the range of grey values. The initial small-scalegradient function gm0_(k)(t) is the same for all smaller scales rangingfrom k=0 through a predefined scale k=S.

As a general rule, the function should have a nominal value in thecentral part of the relevant grey value subrange [t₀, t_(nk−1)], andfall off towards the peripheral parts of the subrange. This empiricalrule ensures that the contrast is high in the most relevant grey valuesubrange and gradually vanishes in lowermost and uppermost subranges, inaccordance with the ‘foot’ and ‘shoulder’ behaviour of common gradationcurves in digital systems [such as disclosed in copending Europeanpatent application EP 02100181.3], but also in screen-film systems,known as the H&D curves.

In the special case where the initial small-scale gradient function ischosen identical to the initial large-scale gradient function, and thefurther described intermediate-scale gradient functions are alsoidentical, then the contrast behaviour is the same as if the initiallarge-scale gradation function y0 _(L)(t)) is applied immediately to thefinal reconstruction result, i.e. if only a single gradation function isapplied in the conventional way.

In accordance with the method of the present invention, it is possibleto differentiate the contrast behaviour, which is mostly related to thesmaller and intermediate scales, from the density mapping behaviourwhich is essentially related to the larger scales, by choosing asmall-scale gradient function that actually differs from the large-scalegradient function. E.g. by specifying the initial small-scale gradientfunction basically identical to the initial large-scale gradientfunction, except in the lower part of the relevant pixel subrange, whereit is made higher, the contrast in the lower densities will increasewithout affecting the contrast in the high densities. This setting isfavourable for enhancing the contrast of trabecular bone structure.Alternatively, the contrast at the skin boundaries can be raised byspecifying the small-scale gradient function having high value in thedarkmost part of the relevant grey value subrange. Such adjustment isrecommended for better visualizing soft tissue lesions near the skinboundary. By specifying a small-scale gradient function that exceeds thelarge-scale gradient function everywhere, overall contrast is reinforcedwithout significantly altering the global distribution of densities(which is determined by the large-scale gradient function).

In a preferred embodiment the small-scale gradient function is specifiedto have a predefined shape independent from the large-scale gradientfunction. This is achieved by specifying predefined function values inthe anchor points.

This way, the range of density levels may be matched to the actual greyvalue range of the image according to predefined histogram percentilesby the method described above, without affecting however the contrast,which depends on an independently specified small-scale gradientfunction.

In an alternative embodiment the initial small-scale gradient functionis predefined by its ordinate values gm0 _(S)(t_(k))=c_(k) in the nkanchor points, expressed as a predefined percentage of the averageinitial large-scale gradient

${gm0}_{Lav} = \frac{{{y0}_{L}\left( t_{{nk} - 1} \right)} - {{y0}_{L}\left( t_{0} \right)}}{t_{{nk} - 1} - t_{0}}$

Initial small-scale gradient values are preferably in the range between10% and 400% of gm0 _(Lav), most preferably c_(k)=100%, 170%, 250%,100%, 25%.

The small-scale gradient function is defined by fitting a piecewisepolynomial function such as a spline or a Bezier curve to the predefinedanchor points. It is extrapolated beyond the range [t₀, t_(nk−1)] byconstant extension segments having ordinate values c₀ and c_(nk−1)respectively.

3c. Initial Intermediate-scale Gradient Functions

Given an initial large-scale gradient function gm0 _(L)(t) at a scale Land an initial small-scale gradient function gm0 _(S)(t) that applies tothe smaller scales from 0 through S as defined above, then the initialgradient functions at the intermediate scales from S+1 through L−1 aregenerated according to the following preferred embodiment:

${{{gm0}_{k}(t)} = {{{gm0}_{S}(t)} \cdot \left( \frac{{gm0}_{L}(t)}{{gm0}_{S}(t)} \right)^{\frac{k - S}{L - S}}}},\mspace{14mu}{k = {S + 1}},{S + 2},\ldots\mspace{11mu},{L - 1}$

This specification of the intermediate scale gradient functions ensuresa gradual transition from the large-scale gradient function to thesmall-scale gradient function. As a consequence, the contrast behaviourevolves gradually from the large-scale contrast behaviour specified bygm0 _(L)(t), to the contrast behaviour specified by gm0 _(S)(t).

In a preferred embodiment, the small-scale parameter S is preferably setwithin the range [0, 4], and L should preferably be in the range [S+2,k_(max)−1], where k_(max) is the largest scale of the multiscaledecomposition. In case the image dimensions are 2048×2048, mostpreferable settings are S=3 and L=7. In that case, the scales 0, 1, 2and 3 are controlled by the same small-scale gradient function gm0_(S)(t), the large-scale gradient function applies to scale 7, and agradual transition is provided from scale 4 through scale 6. An exampleof a series of these functions is illustrated in FIG. 9.

A few alternative embodiments of methods for defining the initialgradient functions gm0 _(k)( ) are described in EP 02102368 filed Sep.18, 2002.

4. Interactive Adjustment of Density and Contrast

An image processed according to the above described multiscale gradationmethod and displayed on a display monitor will have appropriate densityand contrast if the initial multiscale gradient functions gm0 _(k)( )are defined properly.

However, the initial specification of these functions may not beoptimal, or the viewing task at hand may impose special requirements ondensity or contrast in some density band, e.g. the density band thatcorresponds to the lung fields may need more contrast and lower density.

It is possible to independently adjust the density level and thecontrast of all image regions belonging to the specified density band byan interactive procedure in accordance with the findings of the presentinvention.

In an interactive adjustment session, the initial state and thecorresponding displayed image is determined by the series of initialmultiscale gradient functions gm0 _(k)( ) specified by one of themethods described above. With each adjustment induced by a userinteraction an updated series of multiscale gradient functions gm_(k)( )is generated by applying changes to the initial series. Upon everychange the above method of multiscale gradation is applied to theupdated multiscale gradient functions and preferably the resulting imageis displayed to provide the user with feedback about the adjustment.This way, any desired modification of density or contrast in parts ofthe image can be efficiently accomplished by one or more user-inducedadjustments, thereby significantly improving the workflow, also indifficult cases that require critical adjustments.

In a preferred embodiment the density band that requires adjustment isspecified by indicating a point in the initially displayed image thathas the intended density. This can be done using any device meansdenoted by indicium intended for indicating positions in an image, suchas a cursor operated by a computer mouse. The density of the indicatedpoint is denoted by the initial density yr0. The amounts of density andcontrast adjustment denoted by dy and dc are indicated by the movementof a cursor in a window, or by any two-dimensional pointing device orinteractive controller. Preferably, the window in which the cursor canbe moved is the image window, so that the viewer doesn't have to removefocus from the image during adjustment. Alternatively, two separateone-dimensional GUI controls can be used to specify the amounts ofadjustment dy and dc, such as two sliders or scroll bars.

The adjustment parameters specify the amount of density and contrastamplification adjustment to be applied to all pixels that have a densitythat is substantially equal to the initial density yr0. The adjustmentquantities are specified relative to the settings that yield theinitially displayed image. Subsequent adjustment parameters may bespecified still to the initially displayed image, or relative to theresult of the previous adjustment, i.e. subsequent adjustments may beabsolute or incremental. The starting position of the cursor used forspecifying the adjustment parameters is preferably in the center of theimage. Alternatively, it may be a point in a notional coordinate systemwithin the cursor window comprising a density axis in horizontaldirection and a contrast amplification axis in vertical direction, wherethe initial cursor position relative to the coordinate system isindicative of the initial density and contrast amplification of theselected density band.

In a preferred embodiment the adjustment of density and contrastamplification is carried out as described below.

First, the initial small-scale gradient function gm0 _(S)(t) isexpressed in terms of density y instead of grey value t, using therelationship t0 _(L)(y), which is the inverse of the large-scalegradation function y0 _(L)(t).

Next, the small-scale gradient function is locally deformed in ordinatedirection by an amount dc across a subrange centered at the initialdensity yr0, as depicted in FIG. 10. This can be done by representingthe small-scale gradient function by a Bezier curve or a spline andusing common graphical techniques to accomplish a smooth localdeformation. This ensures that the magnitude of deformation is highestat the initial density yr0, and gradually diminishes to zero at theboundaries of the subrange. The wider the subrange that specifies thedensity band, the more pixels of the image will be involved in theadjustment procedure. Preferably, the subrange width is 25% of theoverall density range.

The deformed small-scale gradient function is subsequently expressed interms of grey values t, using the initial large-scale gradation y(t)=y0_(L)(t) as conversion function, yielding an adjusted small-scalegradient function gm_(S)(t).

Next, the density adjustment is applied by locally deforming thelarge-scale gradation function y(t)=y0 _(L)(t) in ordinate direction byan amount dy across a subrange centered at the grey value tr0 thatcorresponds with density yr0, i.e. the t-value for which y0_(L)(tr0)=yr0, as depicted in FIG. 11. This is done in a similar way asthe local adjustment of the small-scale gradient function describedabove.

The thus adjusted large-scale gradation function is denoted by y_(L)(t).The derivative of this function yields the adjusted large-scale gradientfunction gm_(L)(t).

A series of adjusted intermediate-scale gradient functions is obtainedin a similar way as the initial gradient functions, based on theadjusted versions of the small-scale and large-scale gradient functions:

${{{gm}_{k}(t)} = {{{gm}_{S}(t)} \cdot \left( \frac{{gm}_{L}(t)}{{gm}_{S}(t)} \right)^{\frac{k - S}{L - S}}}},\mspace{14mu}{k = {S + 1}},{S + 2},\ldots\mspace{11mu},{L - 1}$

If finally the reconstruction procedure of multiscale gradation isapplied as described higher under the heading ‘Reconstruction andmultiscale gradation’, using the adjusted gradient functions gm_(k)instead of the initial set of functions gm0 _(k), then an image withindependently adjusted density and contrast results, in accordance withthe findings of the present invention.

The multiscale gradient functions and the large-scale gradation functionare preferably specified by means of piecewise polynomials. Thisrepresentation is advantageous for computing a smooth local deformation,or for computing the derivative function. Alternatively, the large-scalegradation function may be specified in the form of a table of coordinatepairs, which is an appropriate representation for computing the inverserelation t0 _(L)(y), thereby avoiding explicit function inversion. Boththe forward and inverse functions are evaluated at arbitrary points bylinear interpolation of the table values. The kind of representation isnot essential and is merely motivated by the mathematical simplicity ofthe operations that must be applied. Transition from one kind ofrepresentation to the other is done by common interpolation techniques.

When applying density adjustment to the large-scale gradation it isimportant to ensure that the resulting function remains monotonic. It isalso preferable to impose limits to the slope of the gradation function,and to the ordinates of the small-scale gradient function in order toavoid excessive contrast amplification.

In a second embodiment of independent adjustment of density and contrastof pixels belonging to a specified density band, referring to FIG. 12, atwo-dimensional graph (60) is displayed that plots small-scale gradientrepresenting contrast as a function of density. At the beginning of anadjustment session, the initial gradient function gm0 _(S)(y) (61) isplotted, along with the histogram (62) as a function of density. Inaddition, a density wedge (63) may be plotted along the density axis toexplicitly display the corresponding density at each abscissa value.

The nominal density of the density band intended to be adjusted isindicated by the user by placing a cursor (64) or other pointing meansat the desired position along the density axis. Upon acknowledgement ofthe thus selected density band, the corresponding point [yr0, gm0_(S)(yr0)] on the contrast function plot is marked as the startingposition (65) for subsequent adjustment. The desired adjustment ofdensity and contrast amplification are indicated by moving a cursor (66)or any other pointing means relative to the marked point, either in avertical direction for specifying contrast adjustment dc, or in ahorizontal direction for specifying density adjustment dy, or in anyother direction for specifying a simultaneous adjustment in proportionto the horizontal and vertical movement components. Each time a set ofadjustment parameters are specified, the series of adjusted gradientfunctions gm_(k)( ) and resulting image are computed as described in thefirst embodiment. Real-time feedback to the user is achieved by updatingthe displayed image (67) on each cursor movement. In addition thecontrast function plot and the histogram may be updated for improvedfeedback.

In a third embodiment, referring to FIG. 12, a two-dimensional graph isdisplayed that plots small-scale gradient representing contrast as afunction of density along with the histogram and a density wedge alongthe density axis, as described in the previous embodiment.

However, the nominal density of the density band intended to be adjustedis indicated by the user by indicating a point (70)in the displayedimage having the same density, as described in the first embodiment.Similarly, the amounts of density and contrast adjustment dy and dc areindicated by the movement of a cursor in the window. The selectednominal density of the density band to be adjusted is marked on thecontrast function plot as the starting position for subsequentadjustment. Upon movement of the cursor that indicates the desiredamount of adjustment, the image, the histogram and the contrast functionare updated, along with the initial marker and the cursor that indicatesthe current adjustment.

1. A method of modifying at least one of contrast and density of pixelsof a processed image comprising the steps of: (a) displaying saidprocessed image on a display screen, (b) specifying an initial densitylevel in said processed image by covering a pixel or pixel region bymeans of a first indicium which is capable of responding to a user inputfor moving said indicium relative to the displayed processed image, thedensity of the pixel or pixel region covered by said indicium being theinitial density, (c) in response to a user input, moving a secondindicium in at least one of two directions relative to the displayedprocessed image, (d) changing the contrast of pixels in the displayedprocessed image which have substantially the same density as saidinitial density upon receiving the user input for movement of saidsecond indicium in a first of said directions, and (e) changing thedensity of pixels in the displayed processed image which havesubstantially the same density as said initial density upon receivingthe user input for movement of said second indicium in a second of saiddirections, wherein contrast and density are changed independently bymodifying a multi-scale representation of said image, wherein themodification is derived from at least two gradient functions determinedat different scales, and wherein a gradient function at a specific scalespecifies how contrast amplification at a scale depends on density. 2.The method according to claim 1 wherein the amount by which the contrastof selected pixels is changed is largest for pixels having a densityequal to said initial density.
 3. The method according to claim 2,wherein the amount by which the density of selected pixels is changed islargest for pixels having a density equal to said initial density. 4.The method according to claim 3, wherein said amount of density changegradually decreases for pixels that have either lower or higher densityvalues relative to the initial density level.
 5. The method according toclaim 1, wherein the amount by which the density of selected pixels ischanged is largest for pixels having a density equal to said initialdensity.
 6. The method according to claim 5 wherein said amount ofdensity change gradually decreases for pixels that have either lower orhigher density values relative to the initial density level.
 7. Acomputer readable medium encoded with a computer executable program codewhich executes the steps of: (a) displaying a processed image on adisplay screen, (b) specifying an initial density level in saidprocessed image by covering a pixel or pixel region by means of a firstindicium which is capable of responding to a user input for moving saidindicium relative to the displayed processed image, the density of thepixel or pixel region covered by said indicium being the initialdensity, (c) in response to a user input, moving a second indicium in atleast one of two directions relative to the displayed processed image,(d) changing the contrast of pixels in the displayed processed imagewhich have substantially the same density as said initial density uponreceiving the user input for movement of said second indicium in a firstof said directions, and (e) changing the density of pixels in thedisplayed processed image which have substantially the same density assaid initial density upon receiving the user input for movement of saidsecond indicium in a second of said directions, wherein contrast anddensity are changed independently by modifying a multi-scalerepresentation of said image, wherein the modification is derived fromat least two gradient functions determined at different scales, andwherein a gradient function at a specific scale specifies how contrastamplification at a scale depends on density.
 8. The computer readablemedium encoded with a computer executable program code according toclaim 7, wherein the amount by which the contrast of selected pixels ischanged is largest for pixels having a density equal to said initialdensity.
 9. The computer readable medium encoded with a computerexecutable program code according to claim 8, wherein the amount bywhich the density of selected pixels is changed is largest for pixelshaving a density equal to said initial density.
 10. The computerreadable medium encoded with a computer executable program codeaccording to claim 9, wherein said amount of density change graduallydecreases for pixels that have either lower or higher density valuesrelative to the initial density level.
 11. The computer readable mediumencoded with a computer executable program code according to claim 7,wherein the amount by which the density of selected pixels is changed islargest for pixels having a density equal to said initial density. 12.The computer readable medium encoded with a computer executable programcode according to claim 11, wherein said amount of density changegradually decreases for pixels that have either lower or higher densityvalues relative to the initial density level.
 13. A user interface foran image processing and display unit comprising: (a) a window wherein aprocessed image is displayed, (b) a first indicium capable of respondingto user input for moving relative to the displayed processed image,wherein the density of a pixel or pixel region covered by movement ofsaid first indicium is an initial density, and (c) a second indiciumcapable of responding to user input for moving in at least one of twodirections relative to the displayed processed image, wherein said userinput for movement of said second indicium in a first direction causes achange of density of pixels in the displayed processed image that have adensity value that is substantially equal to said initial density,wherein said user input for movement of said second indicium in a seconddirection causes a change of contrast of pixels in the displayedprocessed image that have a density value that is substantially equal tosaid initial density, and wherein contrast and density are changedindependently by modifying a multi-scale representation of said image,wherein the modification is derived from at least two gradient functionsdetermined at different scales, and wherein a gradient function at aspecific scale specifies how contrast amplification at a scale dependson density.
 14. The user interface for an image processing and displayunit according to claim 13, wherein the amount by which the contrast ofselected pixels is changed is largest for pixels having a density equalto said initial density.
 15. The user interface for an image processingand display unit according to claim 14, wherein the amount by which thedensity of selected pixels is changed is largest for pixels having adensity equal to said initial density.
 16. The user interface for animage processing and display unit according to claim 15, wherein saidamount of density change gradually decreases for pixels that have eitherlower or higher density values relative to the initial density level.17. The user interface for an image processing and display unitaccording to claim 13, wherein the amount by which the density ofselected pixels is changed is largest for pixels having a density equalto said initial density.
 18. The user interface for an image processingand display unit according to claim 17, wherein said amount of densitychange gradually decreases for pixels that have either lower or higherdensity values relative to the initial density level.